Has presenteda paper onnaturallanguagegenerationKnows atleast threeprogramminglanguagesIs interestedin the ethicalimplicationsof generativeAIIs familiarwith theconcept ofpromptengineeringHassuccessfullydebugged acomplexLLMIs excitedabout thepotential ofLLMs ineducationHas used anLLM tosummarizeresearchpapersHas learneda newlanguage inthe last yearCan namethreedifferent LLMarchitecturesIs optimisticabout thefuture ofhuman-AIcollaborationHasexperiencewith fine-tuning a pre-trained LLMHas used agenerative AImodel for anon-academicpurposeHas apreferred AIresearch toolthey canrecommendCan explain thedifferencebetween causaland maskedlanguagemodelsHas traveledinternationallyto attend thisconferenceHascontributedto an open-source AIprojectCanrecommenda good AI ortech relatedpodcastHaspublishedresearch onmultilingualLLMsHasattended anICMLconferencebeforeHas experiencewith low-resourcelanguages inNLPHas collaboratedon a researchpaper withsomeone from adifferent continentHasparticipated ina hackathonfocused on AIor LLMsHas used agenerative AImodel tocreate art ormusicIs currentlyworking on aprojectinvolving cross-lingual transferlearningHas presenteda paper onnaturallanguagegenerationKnows atleast threeprogramminglanguagesIs interestedin the ethicalimplicationsof generativeAIIs familiarwith theconcept ofpromptengineeringHassuccessfullydebugged acomplexLLMIs excitedabout thepotential ofLLMs ineducationHas used anLLM tosummarizeresearchpapersHas learneda newlanguage inthe last yearCan namethreedifferent LLMarchitecturesIs optimisticabout thefuture ofhuman-AIcollaborationHasexperiencewith fine-tuning a pre-trained LLMHas used agenerative AImodel for anon-academicpurposeHas apreferred AIresearch toolthey canrecommendCan explain thedifferencebetween causaland maskedlanguagemodelsHas traveledinternationallyto attend thisconferenceHascontributedto an open-source AIprojectCanrecommenda good AI ortech relatedpodcastHaspublishedresearch onmultilingualLLMsHasattended anICMLconferencebeforeHas experiencewith low-resourcelanguages inNLPHas collaboratedon a researchpaper withsomeone from adifferent continentHasparticipated ina hackathonfocused on AIor LLMsHas used agenerative AImodel tocreate art ormusicIs currentlyworking on aprojectinvolving cross-lingual transferlearning

Human BINGO: Navigating Generative AI and LLMs Across Languages - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Has presented a paper on natural language generation
  2. Knows at least three programming languages
  3. Is interested in the ethical implications of generative AI
  4. Is familiar with the concept of prompt engineering
  5. Has successfully debugged a complex LLM
  6. Is excited about the potential of LLMs in education
  7. Has used an LLM to summarize research papers
  8. Has learned a new language in the last year
  9. Can name three different LLM architectures
  10. Is optimistic about the future of human-AI collaboration
  11. Has experience with fine-tuning a pre-trained LLM
  12. Has used a generative AI model for a non-academic purpose
  13. Has a preferred AI research tool they can recommend
  14. Can explain the difference between causal and masked language models
  15. Has traveled internationally to attend this conference
  16. Has contributed to an open-source AI project
  17. Can recommend a good AI or tech related podcast
  18. Has published research on multilingual LLMs
  19. Has attended an ICML conference before
  20. Has experience with low-resource languages in NLP
  21. Has collaborated on a research paper with someone from a different continent
  22. Has participated in a hackathon focused on AI or LLMs
  23. Has used a generative AI model to create art or music
  24. Is currently working on a project involving cross-lingual transfer learning